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1 Test of Bayesian belief network and stakeholder involvement Danmarks og Grønlands Geologiske Undersøgelse Miljøministeriet Københavns Energi Københavns Kommune

2 Special issue Editor: Hans Jørgen Henriksen Drawing: Authors and Kristian Rasmussen Cover and cover photos: Kristian Rasmussen and Per Rasmussen Impression: 100 Date: July 2004 ISBN: Price: DKkr inc. VAT Ministry of Environment Geological Survey of Denmark and Greenland, GEUS Øster Voldgade 10 DK-1350 Copenhagen K Denmark Telefone: Telefax: Internet:

3 CONTENTS CONTENTS 3 ACRONYMS 7 CHAPTER 0 Preamble 9 Hans Jørgen Henriksen, GEUS...9 Car start problem with a time delay: Precautionary groundwater protection...9 CHAPTER 1 Summary 13 Hans Jørgen Henriksen, GEUS...13 Introduction...13 Objectives for the Danish case study...14 Results of the Danish case study...15 Evaluation...17 Recommendations for guidelines...18 CHAPTER 2 Sammenfatning 19 Hans Jørgen Henriksen, GEUS...19 Introduktion...19 Formål...20 Resultater af det danske MERIT case studie...20 Evaluering...22 Anbefalinger til vejledning i brug af BBNs...23 CHAPTER 3 Introduction 25 Hans Jørgen Henriksen, GEUS, Per Rasmussen,GEUS, Gyrite Brandt, CE and Dorthe von Bülow, CE Objectives Decision support tool Quantifiable water resource indicators Framework for stakeholder participation Terminology for public participation under the Water Framework Directive Information, consultation and active involvement Public participation in relation to the case study at Havelse wellfield BBN Terminology Definition of Bayesian belief networks Using HUGIN for reasoning under uncertainty Hypotheses to be tested in relation to BBNs Impacts from individual, group and structure variables Concept and approaches applied for the Danish case study Case study area: Havelse wellfield catchment Existing practices at Copenhagen Energy...37 GEUS 3

4 3.5.1 Regional abstraction Local abstraction Concrete groundwater protection Abstraction licenses The test area: Havelse wellfield and catchment area Abstraction licence for the Havelse wellfield Stakeholder involvement Introduction to BBN construction protocol References...46 CHAPTER 4 Description of the wider water resources management in Denmark 49 Lisbeth Flindt Jørgensen (GEUS) and Gyrite Brandt (CE) Danish drinking water production The overall legal and administrative framework Active groundwater protection in Denmark After the implementation of the Water Framework Directive Stakeholder involvement References...55 CHAPTER 5 Stakeholder involvement 57 Per Rasmussen, GEUS Identification of stakeholders Stakeholder involvement process The professional stakeholder group The citizens stakeholder group Stakeholders evaluation of the involvement process...64 Annex 1. Stakeholder questionnaire and input: Distribution of tasks among stakeholders: roles in the context of groundwater protection Annex 2. Stakeholder questionnaire and input: What would be the consequences of different groundwater protection measures? Discussion...72 CHAPTER 6 Development of Bayesian belief networks 73 Hans Jørgen Henriksen, GEUS Background What is a BBN? An example of a BBN for farming contracts Methodology of BBN development Informing stakeholders and general public about precautionary groundwater protection issues and BBN development Construction of BBNs with stakeholder involvement (Steps 1 3) Quantitative BBN construction, data collection and definition of states and CPTs (Steps 4-6) Collection of feedback from stakeholders (Step 7) BBN for groundwater protection Description of the directed acyclic graph for voluntary farming contracts Description of conditional probability tables for BBN for farming contracts...99 GEUS 4

5 6.5.3 Using the BBN model in farming contract decision-making Use of structural learning for assessment of sandy soils vulnerable to pesticide leaching A BBN for flooding Validation of BBNs Validation of the BBN for farming contracts Validation of BBN for flooding References CHAPTER 7 Data collection for groundwater protection management 133 Per Nyegaard, GEUS Basic hydrogeological data Pesticide mapping at field level Sampling of individual (shallow wells) and Havelse creek for pesticides Land use data and restrictions References CHAPTER 8 Main conclusions and perspectives in relation to WFD 151 Hans Jørgen Henriksen, GEUS, Per Rasmussen, GEUS, Gyrite Brandt, CE and Dorthe von Bülow, CE Stakeholder engagement Use of BBN Problems to look out for Future research needs MERIT concept compared to traditional approaches Main ongoing CE activities related to the Water Framework Directive References CHAPTER 9 Comments from the Havelse Creek Citizens' Group on draft GEUS report entitled "Test of Bayesian belief network and stakeholder involvement" 163 Hans Jørgen Henriksen, GEUS Re Chapter 0: Preamble Re Chapters 1 and Re Chapter 3: Introduction Re Chapter 4: Description of the wider water resources management in Denmark Re Chapter 5: Stakeholder involvement Re Chapter 6: Development of Bayesian belief networks Re Chapter 7: Data collection for groundwater protection management Re Chapter 8: Main conclusions and perspectives in relation to WFD Re Appendix 1: Economic loss on conversion to pesticide-free crop cultivation in the Havelse abstraction area Re Appendix 2: Economic analysis of abstraction strategies for groundwater in the Havelse Creek catchment area Re Appendix 3: When citizens are to be involved: From water in the basement to Bayesian networks Re Appendix 4: Contribution from the Havelse wellfield citizens' group References GEUS 5

6 Appendix 1 Driftsøkonomiske tab ved pesticidfri dyrkning af landbrugsarealer ved Havelse kildeplads. Svend Rasmussen, KVL (in Danish) Appendix 2 Samfundsøkonomisk analyse af indvindingsstrategier for grundvand i oplandet til Havelse å. Jesper S. Schou, DMU (in Danish) Appendix 3 Involving citizens: From water in the basement to Bayesian networks. Jan Poulsen, Agenda 21 Center, Frederikssund Appendix 4 MERIT workshop 3 March Comments from the Havelse wellfield citizens group. GEUS 6

7 ACRONYMS Active X AC21 AIS API BAM BBN C C++ CD CE COOF COOP CPT DAG DANVA DB2 DEPA DN DSS EC EDSS EM EU FSL FVD GDP GEUS GIS GMO Harmoni-CA HDE HUR HUGIN HVS KUPA KVL LAS LØJ MAC Collection of separate technologies that facilitate distribution, validation and extensibility of Internet applications Agenda 21 Centre The Danish Areal Information System Application Programming Interface The pesticide metabolite 2,6-dichlorobenzamide Bayesian Belief Network Programming language widely used to develop commercial applications A object-oriented superset of the C language Compact Disc Copenhagen Energy water supply COOperation Forum COOrdination forum for groundwater Protection Conditional Probability Table Directed Acyclic Graph The Danish Water and Waste Water Association Dækningsbidrag II (in Danish) Danish Environmental Protection Agency The Danish Society for the Conservation of Nature (an NGO) Decision Support System European Community Environmental Decision Support System Expectation Maximation (to learn the conditional probabilities in a network based on data) European Union Danish Forest and Landscape Research Institute Organisation of private waterworks in Denmark Gross Domestic Product Geological Survey of Denmark and Greenland Geographical Information System Genetically Modified Organisms Harmonised modelling tools for integrated basin management (Concerted Acition) Hugin Decision Engine The Greater Copenhagen Authority Software for intelligent solutions (www.hugin.com) The Greater Copenhagen Area Water Association Concept for identifying areas where shallow aquifers are vulnerable to pesticide contamination The Royal Veterinary and Agricultural University, Denmark Linear Alkylbenzene Sulphonate The Danish Society of Organic Farmers The Maximum Acceptable Concentration GEUS 7

8 Java Object oriented language similar to C++ LAI Leaf Area Index MERIT Management of Environment and Resources using Integrated Techniques MVJ An agreement supported by EC and national grants for environmentally friendly agriculture, but only in vulnerable agricultureal areas ( SFL areas ) (In Danish: MiljøVenlige Jordbrugsforanstaltninger) NDVI Normalized Difference Vegetation Index NERI National Environmental Research Institute NOLA North Zealand Farmers Union NO 3 Nitrate NGO Non Governmental Organisation OSD Areas of specific drinking water interest PP Public Participation QA Quality Assurance RBMP River Basin Management Plan SH Stakeholder SJFL Zealand Family Farmers Association SNS Danish Forest and Nature Agency SWOT Strengths, weaknesses, opportunities and threats WFD Water Framework Directive WP5 Work Package 5 GEUS 8

9 CHAPTER 0 Preamble Hans Jørgen Henriksen, GEUS Car start problem with a time delay: Precautionary groundwater protection This chapter contains a brief introduction to the Danish MERIT case study. (The MERIT project: Management of the Environment and Resources using Integrated Techniques, contract number EVK1-CT ) At the kick-off meeting, Gyrite Brandt of Copenhagen Energy (CE) explained CE s general view: Our drinking water supply strategy has groundwater as the main source, surface water as a buffer and artificial recharge as a supplement. We have 55 wellfields in the Copenhagen area, of which 31 are suitable, 20 that might be suitable and four unsuitable. Our effort is to restore and protect the suitable wellfields, and the Havelse wellfield belongs to this group. The action options CE has are afforestation, closing wells not in use, establishing monitoring wells, setting up local waterworks cooperation forums and implementing voluntary farming agreements. Because afforestation is not possible to any great extent in the area, we decided to chose farming contracts as the main issue to analyse in the case study. Finn Jensen from the University of Ålborg introduced the audience to Bayesian belief networks by giving the example of a car that won t start 1. Let s say that one morning, my car won t start. I can hear the starter turn over, but nothing happens. There may be several reasons for my problem, but I can hear the starter turn over, so there must be power in the battery. Therefore, the most probable cause is either that the car s petrol was stolen during the night or that the spark plugs are dirty. It could also be due to dirt in the carburator, a leak in the ignition system, or something even more serious. To find out, I first check the fuel gauge. It shows that the tank is half-full, so I decide to clean the spark plugs. To have a computer perform the same kind of reasoning, we need answers to questions such as: What was it that made me conclude that stolen fuel and dirty spark plugs were the two most probable causes? What made me decide to look at the fuel gauge, and how does the observation that the tank is half full make me conclude that it must be the spark plugs? To be precise, we need ways of representing the problem and ways of performing inference in this representation so that a computer can simulate this kind of reasoning and perhaps do it better and faster than humans. 1 Citizens group has pointed out that the car start problem is inadequate, see chapter 9. GEUS 9

10 We must ask ourselves questions about what affects the goal and what affects what during the process. For such a problem, it is necessary to construct a causal network, a so-called Bayesian belief network that shows causes and effects and how they are interconnected. A Bayesian belief network, or BBN, can be used to exclude causes that are improbable and to select the correct actions to be taken. In such a network, nodes are states and arrows are effects, but keep your attention on the direction of the arrows because they indicate what affects what. In a BBN, the arrow symbolises a conditional likelihood. Thus it is possible to carry out calculations of likelihood for the states of different nodes, based on parent nodes. BBNs are especially useful for complex issues. Today we know a great deal about the quality of the deep groundwater from work on a national scale in the groundwater monitoring programme. However, we have little knowledge about a local area like the Havelse wellfield capture zone, and we have no information about the quality of young groundwater. Even if we did, we wouldn t know exactly how shallow-lying contaminated groundwater would affect deep groundwater in the long run. So how can we explain and make decisions about the need for precautionary groundwater protection in an area with long groundwater residence times, when so far no nitrate and pesticides have been reported in the raw water abstracted from the wellfield? It seems as though our Havelse wellfield case study can be compared to having trouble starting your car, but with a built-in time delay. Even if someone has stolen the fuel, or the spark plugs are dirty, our car still starts in the morning, and will continue to do so for a number of years. Then suddenly one morning, we realise that our car will not start any more. Because there are residence times for water moving from shallow groundwater to deep groundwater, there is a delay in feedback in our natural system of several decades or perhaps even half a century. Our knowledge about what happens to pesticides in shallow groundwater is limited, so how can we handle this problem based on the little we do know? Can we use BBNs to encapsulate and communicate this uncertainty and agree upon sound precautionary action, and to build support and understanding in the general public and stakeholders with respect to implementation? How can a BBN be helpful for Copenhagen Energy, who has 55 wellfields? Can it provide useful input for a groundwater protection strategy? We are dealing with a field of study that investigates the impact that individuals, groups, and projects have on the credibility of developed BBNs and the behaviour of stakeholders and the general public. The purpose was to test BBNs as a tool in water resource management, and to suggest guidelines for the use of BBNs and for improving the engagement of stakeholders. We wanted stakeholders and citizens to express the influence they had on the development of the BBNs (variables, links and numbers). We sought an open and positive project management, which allowed discussion of the various elements and permitted suggestions to be incorporated in the construction of a BBN. We wanted to analyse whether BBNs are a good, flexible tool for integration. Do BBNs provide a clear overview, and are they a good tool in a dialogue? There is a pressing need to develop management schemes and approaches that acknowledge the pragmatic character of these problems. We scientists should not simply GEUS 10

11 passively observe and measure, but also assist policymakers in taking better action. This requires the ability to combine, interconnect, link, and analyse information across scientific disciplines. This report is intended as an in-depth analysis of the Havelse well field case study, which was presented to stakeholders and public for the first time in November The final joint meeting was held in March As once expressed by Danish scientist Nicolaus Steno ( ), Beautiful is what we see more beautiful is what we understand most beautiful is what we do not comprehend. We have attempted to provide a thorough description in our report that is rich in detail about the BBN construction and stakeholder engagement. The primary source of information in our case study was our own observations backed up by interviews, questionnaires, minutes of meetings and statements by stakeholders and local residents. Case studies have their drawbacks and are open to the perceptual bias and subjective interpretations of the observers, but we have tried to document everything and include as much detail as we could. The present report is a separate report dealing with the Danish case study, which is one out of four demonstration BBNs in four catchment areas in the UK, Denmark, Spain and Italy, each having different sets of water resource problems. The report on the Danish case will provide input to the final report in the form of experience from the Danish case. Furthermore, the MERIT project will present a set of guidelines for the use of BBNs in integrated water resource management with stakeholder involvement, and these guidelines will be included on a CD with the present report and executable versions of the BBNs developed. The CD will be published in September For more information about MERIT, see The Danish case study has had the following project leading steering committee: Senioradvisor, hydrology Hans Jørgen Henriksen, GEUS (project leader, BBN development) Senioradvisor Per Rasmussen, GEUS (project secretary, stakeholder engagement) Geologist Gyrite Brandt, Copenhagen Energy (responsible for CE inputs, BBN development) Anthropologist Dorthe von Bülow, Copenhagen Energy (stakeholder engagement) Jan Poulsen, Agenda 21 Centre Frederikssund has been appointed by the steering committee as facilitator in relation to the citizen group. Copenhagen, June GEUS 11

12 GEUS 12

13 CHAPTER 1 Summary Hans Jørgen Henriksen, GEUS Introduction The applicability of graphical models (Bayesian belief networks BBNs) in water resource management regarding preventive groundwater protection was investigated in a case study for Havelse wellfield catchment in North Zealand (Figure 1.1). Geological Survey of Denmark and Greenland (GEUS) was the project leader and Copenhagen Energy (CE) the decision-maker and end-user in relation to the BBN case study. CE is the largest water supply company in Denmark. It supplies roughly one million inhabitants in the greater Copenhagen area with drinking water each day. CE operates Havelse wellfield together with 55 other large wellfields located in northern and eastern Zealand (the island on which Copenhagen is located). Three different types of actions have been analysed as means of protecting water resources: 1) voluntary farming contracts, 2) afforestation and 3) establishment of wetlands. For each problem a BBN have been constructed and evaluated with full stakeholder involvement of both a group of professional stakeholders and a citizens group. The possibilities and problems connected with voluntary five-ten-year farmer contracts prescribing no pesticide application in return for compensational payment was especially analysed. It was not a question of actually implementing such zones that was in focus in the study, only analysing what would be required in compensational payment if such zones were to be implemented at a magnitude and on a scale that allowed them to function as efficient groundwater protection. Furthermore, the aim was to clarify the impact implementation of such protection zones could have on land use, farm economics, groundwater quality, biodiversity and aquatic environment. Information, consultation and active involvement of professional stakeholders and general public was carried out using announcements, facilitated public meeting, working group meetings, newsletters, a Web site, individual meetings and a joint working group. The facilitator of the public meeting and workshops was the Agenda 21 Centre in Frederikssund. Various subcontractors have participated in the project, e.g. Svend Rasmussen (KVL: farm economics) and Jesper Sølver Schou (NERI: value of biodiversity, land use, etc.). GEUS 13

14 EU WFD test catchment Wellfields Figure 1.1 Danish case study area Havelse river catchment (approximately 100 km 2 ). Havelse wellfield capture zone (35 km 2 ) is located in the downstream end of the river basin near Roskilde fiord. Copenhagen Energy operates two other large wellfields upstream at Strø and Attemose. Objectives for the Danish case study The specific objectives of the Danish case study was formulated as follows: 1. To construct a Bayesian belief network (BBN) study site in Denmark with a focus on innovative actions for precautionary groundwater protection against pesticide threats. 2. To investigate the extent to which BBNs can be used as a decision support tool for water resource management at a wellfield abstracting groundwater from the downstream part of a river basin. 3. To develop techniques to encourage and enable full stakeholder involvement in the construction of BBNs. This final but critically important component will provide an evaluation of the most effective means to involve stakeholder groups in the decisionmaking process. GEUS 14

15 Results of the Danish case study Objective 1 Construction of BBN study site: The project provided clear feedback to regional authorities and the larger waterworks in Denmark that the way forward should not be based on voluntary agreements that are individually negotiated with farmers. Action planning based on voluntary agreements is a big issue, but in practice when it comes to implementation, they are not useful. It is much better for Copenhagen Energy either to look for possible afforestation areas or to buy land in the well catchment zone, where there is a certain need due to vulnerable areas (expropriation). Another option will be to auction off farming contracts, simply assigning contracts at a fixed price (e.g. EUR 200/ha) to the farmers who have the highest priority with respect to pesticide application and vulnerability. Objective 2 Test of BBNs as decision support tool: The results of the Havelse BBN study site experience showed a paradox. On the one hand, Bbn s can create space for an open and non-deterministic dialogue with stakeholders due to the flexibility of the decision support tool. This allowed factors (nodes), associations (directed links) and probabilities of the graphical model to be adjusted, reconstructed and validated throughout the process and based on inputs from all involved stakeholders and experts. This means that BBN s were powerful for integrating data and knowledge from different domain experts and capable of handling uncertain information in a practical and easy understandable manner. Constructing the qualitative part of a belief network (nodes and links), although elaborate, seemed relatively straightforward and experts seemed comfortable doing so. This part of the net was relatively easily communicated to stakeholders. On the other hand getting stakeholders, general public and even experts to understand and accept the idea behind BBN s used for decision making was a demanding task. Especially the required probability assessments for the BBN s were not easy to understand or accept by stakeholders. Even domain experts had problems to express all these probabilities numerically, something they were reluctant to do. So the quantitative part, with the probabilities over the variables, were more problematic. However, BBN s may still be useful in the hands of water resource scientists and water managers dealing with complex problems by permitting carefully elicited expert knowledge as a practical alternative to hard data, and facilitating extension of models to ecological and socio-economical endpoints. This leads us to the following conclusions regarding BBNs as a decision support tool. BBNs demonstrated several advantages compared to traditional approaches. BBNs enabled locally based solutions (more than before). They provided local acceptance of decisions and solutions and improved the dialogue between the water company, local stakeholders and authorities. They encouraged diverse perspectives (and thus identified issues not thought of). They enabled a better evaluation of the issues. They made use of local and citizen knowledge not known by the authorities. GEUS 15

16 The weaknesses of BBNs as a decision support tool were the time-consuming and long-lasting process in construction and evaluation of BBNs, which had to be properly organised and conducted. This means that, if there is a lack of resources (time, money, staff), rules for participation, in-depth involvement of authorities, hands-on BBN for the stakeholders and professional supervision of the stakeholder involvement process, then the credibility of the BBNs are likely to be questioned by stakeholders and general public. Objective 3 Techniques to encourage and enable full stakeholder involvement: Regarding involvement of stakeholders and general public in BBN development we made the following observations in the Danish case study: Stakeholders had an impact on the BBN development (on variables, links and CPT s, e.g. perception of vulnerability variable and behaviour of farmers in relation to compensation payment) Evaluation of BBNs with input from stakeholders and general public was a necessary step. In the early, more qualitative stages, broader groups of stakeholders and the general public provided relevant input to BBN development. In the later, more quantitative stages, it was better to consult stakeholders and members of the general public at individual meetings or maybe in stakeholder and citizens groups that each focused on a domain of interest because they were reluctant to give quantitative inputs in larger groups. Experts were necessary for quantitative input to BBNs. In the case study, we had two experts in farming economics and socioeconomics in addition to the geological and hydrological experts from CE and GEUS. It would have been an advantage in BBN development if the panel of experts had included an expert on biodiversity and/or pesticide-exposed aquatic environment as well. The results of BBNs must be followed by a detailed description of the parameters used and why, plus a description of the results and their consequences in order to make BBNs as transparent as possible. It is much to risky to allow politicians or civil servants to make decisions based on the "naked" data. So one should rather allow stakeholders and citizens to become more involved It was important to provide users with more easily understandable explanations of the results, for which numbers not necessarily was the best option and verbal communication are a necessary alternative. Furthermore, an expert s assessments may reflect various biases, where an expert consistently gives probability assessments that are higher or lower than the true probabilities. In order to provide a credible BBN it was necessary to engage stakeholder groups in the validation of BBN s. This was a crucial and demanding task. In conclusion, the use of BBNs went beyond information and consultation and required the full involvement of stakeholders in their construction and validation. The advantage was a reduced risk of later support by stakeholders during the implementation phase of a given action plan. The benefits of BBNs were greatest when there was a high degree of interaction between researchers, users, water managers, stakeholders and general public. GEUS 16

17 Evaluation Even though stakeholders and citizens generally expressed disappointment with participation in the project and in the working groups, including the roles played by GEUS, CE and the Agenda 21 Centre, most stakeholders and citizens also felt that they had had an influence on the development of the BBNs. Some remarks were: The project management was open and positive about discussing the elements. CE and GEUS found out that farming contracts are not an applicable solution. They listened to suggestions. According to stakeholders and citizens, the greatest advantages of the BBNs were the following: Used properly, a good, flexible tool for integration Clear overview Good tool for dialogue The citizens' group can understand a BBN just fine if it is explained properly by the specialists. The greatest limitations of BBNs: Require insight and understanding You get the answers you want Not applicable to groundwater protection Selection of precise data required Correctness of information is questioned A complex tool whose primary strength is as a tool for dialogue Number of variables must not be too large or overview is lost and relationships less clear GEUS 17

18 Recommendations for guidelines Based on the Danish case study and various analysis the following inputs to guidelines was identified: Objective 1 To construction of BBN study site in Denmark A protocol for the development of a BBN is recommended. This protocol prescribes seven steps: 1) define the context, 2) identify factors, actions and indicators, 3) build a pilot network, 4) collect data, 5) define states, 6) construct conditional probability tables and 7) collect feedback from stakeholders and general public. Structural learning or EM-learning is encouraged in order to bridge data and the model developed. Objective 2 To investigate the extent to which BBNs can be used as a decision support tool for water resource management BBNs are most powerful when integrating different domains, e.g. physical, social, economic and ecological, in the early stages of preparing a management plan with the involvement of stakeholder groups and general public A panel of experts is valuable in covering each domain included, for providing proper input and/or for reviewing the results from the BBNs developed. Objective 3 To develop techniques to encourage and enable full stakeholder involvement in the construction of BBNs Clear rules of the game are important: it is necessary to prepare a stakeholder involvement plan describing how to involve stakeholders and general public which is balanced with respect to problem framing and the type of decision support system used for the planning and/or implementation. It is better to involve stakeholders and general public in temporary groups or in individual meetings when direct input is required, especially when collecting data for BBNs; feedback on states, links and CPTs than it is to run the process with broad, permanent working groups of stakeholders and citizens. Don t be afraid of actively involving citizens: but be careful to inform and explain properly about the tasks and goals and do always allow feedback and comments on the BBN development process by presenting the graphical model and easily understood descriptions and results. If representatives of the general public are involved, be sure there is enough time and money to run the process according to the stakeholder involvement plan. GEUS 18

19 CHAPTER 2 Sammenfatning Hans Jørgen Henriksen, GEUS Introduktion Anvendelighed af grafiske modeller (Bayesianske belief netværker BBNs) i vandressourceforvaltning i forbindelse med forebyggende grundvandsbeskyttelse blev undersøgt i et case studie for oplandet til Havelse kildeplads i Nordsjælland (figur 1.1). Danmark og Grønlands Geologiske Undersøgelse (GEUS) var projektleder og Københavns Energi (CE) beslutningstager og slutbruger i relation til BBN case studiet. CE er det største vandforsynings-selskab i Danmark. CE forsyner rundt regnet en million indbyggere i det Storkøbenhavnske område med drikkevand hver dag. CE driver Havelse kildeplads sammen med 55 øvrige store kildepladser på Nordøstsjælland. Tre forskellige indsatsområder er blevet analyseret ved opstilling af BBNs: 1) frivillige dyrkningsaftaler, 2) skovrejsning og 3) etablering af vådområder. For hver problemstilling blev der med fuld involvering af såvel en professionel interessentgruppe som en borgergruppe konstrueret og evalueret et BBN. Muligheder og problemer tilknyttet frivillige fem-ti-årige dyrkningsaftaler der foreskriver nul pesticidanvendelse til gengæld for kompensationsbetaling blev specielt analyseret. Opgaven var ikke konkret at implementere sådanne zoner, men blot at analysere hvad der krævedes i betalingsniveau, såfremt sådanne beskyttelseszoner skulle kunne implementeres med et omfang og i en skala, der kunne medføre at de bidrog effektivt til forbedret grundvandsbeskyttelse. Derudover var hensigten at klargøre, hvilke konsekvenser implementeringen af sådanne nul-pesticid aftaler måtte have på arealanvendelse, driftsøkonomi (i landbruget), grundvandskvalitet, biodiversitet og det akvatiske miljø. Information, konsultation og aktiv involvering af professionelle interessenter og offentligheden (lokale borgere) blev gennemført ved hjælp af annoncer, faciliteret offentligt møde, arbejdsgruppe møder, nyhedsbreve, hjemmeside, og en joint arbejdsgruppe. Agenda 21 Center i Frederikssund var udpeget som facilitator for det offentlige møde og arbejdsgruppemøderne (borgergruppen). Desuden deltog eksterne eksperter i driftsøkonomi (Svend Rasmussen, KVL) og værdisætning af biodiversitet mm. (Jesper Sølver Schou, NERI). GEUS 19

20 Formål De specifikke formål med det danske MERIT case studie var: 1. At konstruere et BBN test studie område i Danmark med fokus på forebyggende grundvandsbeskyttelse (innovative løsninger) i forhold til pesticider i grundvandet 2. At undersøge i hvilket omfang bayesianske belief net (BBNs) var anvendelige som beslutningsstøttesystem i vandressourceforvaltningen for en kildeplads beliggende i nedstrøms del af et vandløbsopland 3. At udvikle metoder der opmuntrede til og gav mulighed for aktiv involvering af interessenter ved konstruktionen af BBNs. Denne sidste men kritiske komponent skulle bidrage til en evaluering af effektive værktøjer til involvering af interessentgrupper i beslutningsprocessen Resultater af det danske MERIT case studie Formål 1 Konstruktion af BBN test studie område. Projektet gav en utvetydig tilbagemelding til regionale myndigheder og større vandværker i Danmark om at vejen frem ikke går via frivillige dyrkningsaftaler som forhandles individuelt med landmænd. Indsatsplaner baseret på individuelle dyrkningsaftaler er et område med et betydeligt potentiale, men når det kommer til implementering af sådanne aftaler, er de ikke brugbare i praksis. Det er meget mere hensigtsmæssigt for CE enten at kigge sig om efter egnede skovrejsningsområder eller at opkøbe jord i oplandet til en kildeplads, hvor der er et særligt behov herfor som følge af særligt sårbare arealer (altså i stedet basere grundvandsbeskyttelsen på ekspropriation). Formål 2 Test af BBNs som beslutningsstøtte system. Resultaterne af undersøgelsen af BBNs for Havelse kildepladsopland viste et paradoks. På den ene side kunne BBNs skabe et rum for en åben dialog (hvor resultatet ikke var givet på forhånd) med interessenter på grund af den fleksibilitet som dette beslutningsstøtte system har. Derved kunne styrende faktorer (knudepunkter/variable), sammenhænge (kanter/links) og sandsynlighedstabeller tilhørende den grafiske model justeres, rekonstrueres og valideres gennem hele processen og på basis an inputs fra involverede interessenter og eksperter. Det vil sige, at BBNs var stærke når det gjalt integration af data og viden fra forskellige domæne eksperter og tilmed var i stand til at håndtere usikkerhed på en praktisk og let forståelig måde. Konstruktionen af den kvalitative del af et BBN (variable og links) var, om end tidskrævende, lige ud af landevejen og eksperter syntes ikke at have væsentlige problemer med denne del. Det var relativt let at kommunikere med interessenterne vedrørende denne del af BBNs. På den anden side, var det en krævende opgave at få interessenter, borgere og eksperter til at forstå og acceptere den tilgrundliggende idé bag BBNs anvendt som beslutningsstøtte værktøj. Specielt var det svært for interessenterne at forstå og acceptere de nødvendige sandsynlighedstabeller. Selv domæne eksperter havde svært ved at formulere disse sandsynligheder numerisk, noget de ofte var tilbageholdende med at gøre. Det vil sige den kvantitative del, de betingede sandsynlighedstabellerne, gav problemer. GEUS 20

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